Aggregate Demand Modeling of Thermostatically Controlled Loads
Conference Year
January 2023
Abstract
Increased renewable and distributed energy resource (DER) penetration in the power grid reduces system inertia making the power grid more sensitive to power imbalances and reducing overall grid reliability. Demand response would help ensure the reliable operation of the electric grid. To evaluate different demand response strategies appropriate models appropriate modelling is needed. This work looks at modeling of the aggregate response of thermostatically controlled loads under varying ambient weather conditions. Different models are compared to the fleet micro-model (modelling each load individually) and the uncertainty in the load estimate quantified.
Primary Faculty Mentor Name
Mads Almassalkhi
Status
Graduate
Student College
College of Engineering and Mathematical Sciences
Program/Major
Electrical Engineering
Primary Research Category
Engineering and Math Science
Aggregate Demand Modeling of Thermostatically Controlled Loads
Increased renewable and distributed energy resource (DER) penetration in the power grid reduces system inertia making the power grid more sensitive to power imbalances and reducing overall grid reliability. Demand response would help ensure the reliable operation of the electric grid. To evaluate different demand response strategies appropriate models appropriate modelling is needed. This work looks at modeling of the aggregate response of thermostatically controlled loads under varying ambient weather conditions. Different models are compared to the fleet micro-model (modelling each load individually) and the uncertainty in the load estimate quantified.